Professor Emeritus of Computer Science

Research

After an undergraduate thesis on “Undecidable Theories” at Harvard under Alan Cobham, I migrated to MIT, where I am pleased to have participated in the early robotics “Copy Demo” milestone. My Ph.D. thesis, under Pat Winston in the Artificial Intelligence Laboratory, was actually in Machine Vision. However, I have spent most of my career in the Artificial Intelligence side of the field that became known as Constraint Programming.

I have sought to confront the fundamentally intractable nature of Constraint Satisfaction Problems (CSPs), in particular by taking advantage of problem structure. I have worked on various extensions of the basic CSP paradigm. For a 1996 ACM Workshop on Strategic Directions in Computing Research, I developed something of a rough roadmap for progress towards what I termed the “Holy Grail” of fully automated problem solving, and in an invited talk at the 2001 Constraint Programming Conference in Cyprus I emphasized the importance of such automation to increase the usability of Constraint Programming. This has helped shape my research agenda.

Some highlights of my contributions to Constraint Programming, often with excellent collaborators, of course:

Foundations: The fundamental k-consistency hierarchy, and extensions to (i,j), inverse, and bounded consistency; the first tractable subclass of CSP’s, and its extension to k-trees; the first complexity analysis of consistency processing; interchangeability, an early form of symmetry; new inference and search methods, including more efficient consistency processing, decomposition, abstraction and reformulation.

Extensions: Early work on “soft constraints” and optimality, agent-based and parallel CSP, conditional, dynamic, composite, ordinal, adversarial and multi-dimensional CSP.

Automation: Early work on automating problem acquisition and model debugging, the choice of solution methods, and the explanation of success or failure.